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Justin Sandefur is a senior fellow at the Center for Global Development. Prior to joining CGD, he spent two years as an adviser to Tanzania's national statistics office and worked as a research officer at Oxford University's Centre for the Study of African Economies. His research focuses on a wide range of topics, including education, poverty reduction, legal reform, and democratic governance.

Intensive and potentially unethical marketing of infant formula is believed to be responsible for millions of infant deaths in low- and middle-income countries (LMICs), yet to date there have been no rigorous analyses that quantify these effects. Paul Gertler and colleagues drew on a sample of 2.48 million births in 46 countries, indicating that the introduction of Nestlé infant formula, the largest supplier worldwide, may have resulted in approximately 66,000 infant deaths in LMICs in 1981—the peak of the infant formula controversy—among households without clean water access. This suggests that unclean water inappropriately mixed into formula acted as a vector for the transmission of water-borne pathogens to infants.

New results from a famous experiment in Kenya have sparked heated debate over whether lump-sum cash transfers have any long-term benefits for those who get them, or even do harm to neighbors who don’t.

One-quarter of the world’s school-age children live in East Asia and the Pacific. In the past 50 years, some economies in the region have successfully transformed themselves by investing in the knowledge, skills, and abilities of their workforce. Through policy foresight, they have produced graduates with new levels of knowledge and skills almost as fast as industries have increased their demand for them. Yet, tens of millions of students in the region are in school but not learning. In fact, as many as 60 percent of students remain in systems that are struggling to escape the global learning crisis or in systems where performance is likely poor.

While I think it's silly to argue we spend too much on girls' education, perhaps it's reasonable to ask whether a concern with gender equality and a cold hard look at recent data would lead anyone to put their marginal dollar into girls' schooling over, say, campaigning for gender quotas (which seem to work well in Indian politics, at least) or even subsidized childcare (which has boosted female labor force participation in Latin America).

In this paper we examine how policymakers and practitioners should interpret the impact evaluation literature when presented with conflicting experimental and non-experimental estimates of the same intervention across varying contexts. We show three things. First, as is well known, non-experimental estimates of a treatment effect comprise a causal treatment effect and a bias term due to endogenous selection into treatment. When non-experimental estimates vary across contexts any claim for external validity of an experimental result must make the assumption that (a) treatment effects are constant across contexts, while (b) selection processes vary across contexts. This assumption is rarely stated or defended in systematic reviews of evidence. Second, as an illustration of these issues, we examine two thoroughly researched literatures in the economics of education—class size effects and gains from private schooling—which provide experimental and non-experimental estimates of causal effects from the same context and across multiple contexts.

We investigate heterogeneity across beneficiaries and implementers—in a randomized trial of contract teachers in Kenyan schools. The data show a stark contrast in success
between the government and NGO arm that can be traced back to implementation constraints and political economy forces put in motion as the program went to scale.

It was a big deal when various media outlets declared last week that the evidence to support mass deworming had been “debunked.” The debate now is not about whether children sick with worms should get treated (everyone says yes), but whether the mass treatment of all kids — including those not known to be infected — is a cost-effective way to raise school attendance. The healthiest parts of the debate have been about the need for transparency, data sharing, and more replication in science. Here, we’re going to focus here on the narrower question of the evidence for mass deworming specifically, which is where some journalists have gotten things quite wrong.

On May 29, 2013, British immigration officers raided the Alternative Tuck Shop, a café just down the road from Oxford University’s economics department, where South Asian and Middle Eastern employees serve tea, scones, and sandwiches. The agents seized two young men, one from Bangladesh and one from Algeria, under suspicion of working in the United Kingdom without authorization. And they shuttered the business temporarily, meaning that hungry Oxford economists would have to walk farther down Holywell Street for their midday panini.

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After one year, public schools managed by private contractors in Liberia raised student learning by 60 percent, compared to standard public schools. But costs were high, performance varied across contractors, and contracts authorized the largest contractor to push excess pupils and underperforming teachers onto other government schools.

Public employees in many developing economies earn much higher wages than similar private-sector workers. These wage premia may reflect an efficient return to effort or unobserved skills, or an inefficient rent causing labor misallocation. To distinguish these explanations, we exploit the Kenyan government’s algorithm for hiring eighteen-thousand new teachers in 2010 in a regression discontinuity design. Fuzzy regression discontinuity estimates yield a civil-service wage premium of over 100 percent (not attributable to observed or unobserved skills), but no effect on motivation, suggesting rent-sharing as the most plausible explanation for the wage premium.

Internationally comparable test scores play a central role in both research and policy debates on education. However, the main international testing regimes, such as PISA, TIMSS, or PIRLS, include very few low-income countries. For instance, most countries in Southern and Eastern Africa have opted instead for a regional assessment known as SACMEQ. This paper exploits an overlap between the SACMEQ and TIMSS tests—in both country coverage, and questions asked—to assess the feasibility of constructing global learning metrics by equating regional and international scales. I ﬁnd that learning levels in this sample of African countries are consistently (a) low in absolute terms; (b) signiﬁcantly lower than predicted by African per capita GDP levels; and (c) converging slowly, if at all, to the rest of the world during the 2000s. Creating test scores which are truly internationally comparable would be a global public good, requiring more concerted effort at the design stage.

Across multiple African countries, discrepancies between administrative data and independent household surveys suggest official statistics systematically exaggerate development progress. We provide evidence for two distinct explanations of these discrepancies.

In this paper we examine how policymakers and practitioners should interpret the impact evaluation literature when presented with conflicting experimental and non-experimental estimates of the same intervention across varying contexts. We show three things. First, as is well known, non-experimental estimates of a treatment effect comprise a causal treatment effect and a bias term due to endogenous selection into treatment. When non-experimental estimates vary across contexts any claim for external validity of an experimental result must make the assumption that (a) treatment effects are constant across contexts, while (b) selection processes vary across contexts. This assumption is rarely stated or defended in systematic reviews of evidence. Second, as an illustration of these issues, we examine two thoroughly researched literatures in the economics of education—class size effects and gains from private schooling—which provide experimental and non-experimental estimates of causal effects from the same context and across multiple contexts.